A New Explanation For the Plight of Winter Babies

Ant passes along a Wall Street Journal report on research that turned up a new explanation for the lifelong challenges experienced by winter babies. "Children born in the winter months already have a few strikes against them. Study after study has shown that they test poorly, don't get as far in school, earn less, are less healthy, and don't live as long as children born at other times of year. Researchers have spent years documenting the effect and trying to understand it... A key assumption of much of that research is that the backgrounds of children born in the winter are the same as the backgrounds of children born at other times of the year. ... [Economist] Mr. Hungerman was doing research on sibling behavior when he noticed that children in the same families tend to be born at the same time of year. Meanwhile, Ms. Buckles was examining the economic factors that lead to multiple births, and coming across what looked like a relationship between mothers' education levels and when children were born." Here's a chart in which the effect — small but significant — jumps out unmistakeably.

Comments

Jumps out?

[ucblockhead]

Of course the difference jumps out. The chart was deliberately designed to make the change jump out by not using 0 as the origin of the Y axis.

This is a very common technique for making a difference look a lot larger than it actually is.

Re:Jumps out?

[wjh31]

Much more important is the lack of error bars, they are what you can use to decide if the difference is greater than noise. However since they seem to be confident enough to include a secondary maximum and minimum, we are led to assume that the error bars are rather small. Since TFA says the study looked at 52 million children over 12 years, it sounds fairly reasonable to suggest that error bars are relatively small w.r.t atleast the primary max an min.

Re:Jumps out?

[AliasMarlowe]

Did they use only data for Northern hemisphere women (north of the tropics)?, Or is it a mix with tropical and Southern hemisphere as well?

Re:Jumps out?

[selven]

It's well known that children born in Jan/Feb/Mar are much more likely to get ahead because age cutoffs tend to be January 1, so kids born on Jan 1 compete with kids born on Dec 29 in the same year despite having 11 months more experience. Because of this, more attention is given to these "stars", and they perform higher. You should look at the birth months of some professional football teams.

Re:Jumps out?

[icebike]

From TFA:

The two economists examined birth-certificate data from the Centers for Disease Control and Prevention for 52 million children born between 1989 and 2001, which represents virtually all of the births in the U.S. during those years. The same pattern kept turning up: The percentage of children born to unwed mothers, teenage mothers and mothers who hadn't completed high school kept peaking in January every year. Over the 13-year period, for example, 13.2% of January births were to teen mothers, compared with 12% in May -- a small but statistically significant difference, they say.
--end-quote

So problem is more than adequately explained by being born to a teen mother, and winter birth need not be related at all.

Winter birth is probably attributable to spring break, and the re-emergence of summer fashions (read: skimpy) and horny young guys after a hard winter.

The real story is births to teen mothers burdens not only the mother, but also the baby. Winter has nothing to do with it.

Re:Jumps out?

[Rob the Bold]

Much more important is the lack of error bars, they are what you can use to decide if the difference is greater than noise. However since they seem to be confident enough to include a secondary maximum and minimum, we are led to assume that the error bars are rather small. Since TFA says the study looked at 52 million children over 12 years, it sounds fairly reasonable to suggest that error bars are relatively small w.r.t atleast the primary max an min.

TFA also says that the 52 million children in the sample were all of them, making the sample 100% of the population. That should result in some pretty small error bars, indeed!

The two economists examined birth-certificate data from the Centers for Disease Control and Prevention for 52 million children born between 1989 and 2001, which represents virtually all of the births in the U.S. during those years.

Re:Jumps out?

[pla]

Since TFA says the study looked at 52 million children over 12 years, it sounds fairly reasonable to suggest that error bars are relatively small w.r.t atleast the primary max an min.

With an n of 52 million, those charts do include error bars - They fall about +/- a thousandth of a pixel around each plotted point. The pixels themselves just cover the error bars.

As for the Y-offset... Yes, you can use that to dishonestly highlight minor difference. When you have such small differences in your dependent variable, however, as long as you make the Y axis entirely clear to the reader, it merely serves to save the viewer a trip to find a magnifying glass.

Basically, if you had a series that showed some degree of noisy periodicity and you zoomed/cropped in on one section that appears to prove your point, it counts as dishonest. When you have virtually no error and a trend that looks like cookie-cutter copies from year to year - I'd love to see the p values for this, but I'd bet it would require scientific notation to realistically print (ie, on the order of p <= 10^-12).

Re:Jumps out?

[davidphogan74]

The moderator was probably born in January, and thus unable to get the question.

That means...

[Anonymous Coward]

There's a tendency for promiscuous, uneducated teenagers to have unprotected sex during springtime and early summer. It's always easy to say this, but, duh...

Re:Born in December

[retech]

You could do better... if you were born in June.

Different metric

[HangingChad]

If you count backward from January, that puts conception around April/May. Right around graduation. So if you suppose the poor and less educated would be getting married and starting a family instead of getting ready for college, that might explain some of it.

It would probably be just as interesting to track the birth rates correlated to surges in beer and Jagermeister sales.

Correlation is NOT causation

[Anonymous Coward]

The real causative in winter babies is that babies born under winter's astrological signs have shorter lifelines.

Conception in July/August

[Bwian_of_Nazareth]

I see the explanation in the fact that married and educated women have sex with their man only once a year during their holiday in July/August. :)

Winter where?

[xirusmom]

I wonder if all the data comes from the North Hemisphere? What happens in the south?

School entrance age cutoffs, maybe?

[e9th]

The age cutoff for entry to kindergarten seems to cycle around mid-September, but varies quite a bit from state to state. But in general, a kid born in the winter will have to wait longer to start school.

Re:Born in December

[Anonymous Coward]

I was born in December and pursuing double masters with GPA of 3.4 is it really bad?

I was born in June, and received a Ph.D by the time I was 27, with a 3.95 GPA. Luckily for me, part of that Ph.D training involved learning that the word data is not the plural of anecdote.

It's a good thing, too, because your comment might otherwise serve as the first brick in the foundation of my claim that summer babies are caustic and monumental shitheads that seem to spend their free time in pissing matches.

Re:Unwed mothers?

[pgillan]

Now, correlation is not causation. It's possible that the parent's strong marriage does not *cause* the child's good prospects and performance, but rather that both are caused by some of the same socioeconomic factors

I like the idea that it's actually a reverse correlation- that stupid children with poor prospects and bad grades cause their parents' divorces.

Re:Correllation is Not Causation

[ceoyoyo]

Sigh. Correlation means one of three things with regard to causation. In this case those are:

a) being born in the winter causes increased risk of health and education problems for the baby
b) the baby's increased risk of health and education problems causes him or her to be born in the winter (clearly ridiculous)
c) a third factor causes the baby to both be born in the winter and have increased risk of health and education problems.

The correlation between birth month and risk of health and education problems has been observed. This study is pointing out that the direct causative option (a) is probably not true since they have found possible third factors (c) that appear to influence birth month and are known to have an effect on the risk of health and education problems.

In other words, the study is saying, with actual data and without the childish, misunderstood slogans, the same thing you are - birth month does not cause increased risk of health and education problems.

Showing correlation is required for establishing a causative link between two observations so no, correlation studies do not "need to die." It would be nice if people (including you) understood them a little better though.